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Artificial intelligence 人工智慧

Leveraging AI to advance the power of facts.


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Artificial intelligence at The Associated Press

The Associated Press is one of the first news organizations to leverage artificial intelligence and automation to bolster its core news report. Today, we use machine learning along key points in our value chain, including gathering, producing and distributing the news. Explore this page to learn more about the history of artificial intelligence at The Associated Press, our strategy around the technology and how we use it today.

Innovative at the core

Our foray into artificial intelligence began in 2014, when our Business News desk began automating stories about corporate earnings. Prior to using AI, our editors and reporters spent countless resources on coverage that was important but repetitive and, more importantly, distracted from higher-impact journalism. It was this project that enabled us to experiment with new initiatives and led to other news organizations looking to AP for ways to adopt the technology themselves.
我們對人工智慧的進軍始於 2014 年,當時我們的商業新聞部門開始自動發布有關企業盈利的報導。在使用人工智慧之前,我們的編輯和記者花費了無數資源進行重要但重複的報道,更重要的是,分散了對影響力更高的新聞報道的注意力。正是這個計畫使我們能夠嘗試新的舉措,並促使其他新聞機構向美聯社尋求自行採用該技術的方法。


AI Strategy 人工智慧策略

AP looks for ways to carefully deploy artificial intelligence in areas where we can be more efficient and effective, including news gathering, the production process and how we distribute news to our customers.


AI Strategy 人工智慧策略

AP looks for ways to carefully deploy artificial intelligence in areas where we can be more efficient and effective, including news gathering, the production process and how we distribute news to our customers.

News production 新聞製作

Our objective in production is to streamline workflows to enable our journalists to concentrate on higher impact work. This ranges from the automatic transcription of video to experimenting with the automatic-generation of video shot-lists and story summaries. We also automate some corporate earnings and sports stories.


News distribution 新聞發布

In distribution, we aim to make it easier for our customers to access our content and put it into production faster. As part of this, we are working to optimize content via image recognition, creating the first editorially-driven computer vision taxonomy for the industry. This tagging system will not only save hundreds of hours in production but help surface content more easily.


Startup partners 創業夥伴

AP works with a variety of startups to infuse external innovation into the organization and help to bring our artificial intelligence projects to life. This allows us to experiment at low costs with emerging tech and support the entrepreneurial news ecosystem at the same time. In addition to working with various startups, we also build partnerships to help extend the reach of our journalism and our work with AI. Some key examples include Social Starts, Matter Ventures and NYC Media Lab.
AP 與各種新創公司合作,將外部創新註入組織中,並幫助將我們的人工智慧專案變為現實。這使我們能夠以低成本試驗新興技術,同時支持創業新聞生態系統。除了與各種新創公司合作外,我們還建立合作夥伴關係,以幫助擴大我們的新聞業和人工智慧工作的影響力。一些重要的例子包括 Social Starts、Matter Ventures 和 NYC Media Lab。

AI-powered search 人工智慧驅動的搜尋

AI-powered search makes it easier for users to find the best photos and videos that meet their search criteria. Rather than a traditional metadata search, the tool understands descriptive language and produces search results based on the description a user provides.

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Ongoing projects 正在進行的項目

Check out some of the many projects we are working on below.

Local News AI initiative

The AP distributed a score card to U.S. local news operations to understand AI technologies and applications that are currently being used and how AI might augment news and business functions. Based on the score card results, AP wrote a report and designed an online course to share best practices and techniques on AI with local newsrooms. The initiative’s third phase will be a consultancy program with 15 news operations.
美聯社向美國當地新聞機構分發了一張記分卡,以了解當前正在使用的人工智慧技術和應用程序,以及人工智慧如何增強新聞和商業功能。根據記分卡結果,美聯社撰寫了一份報告並設計了一個線上課程,與當地新聞編輯室分享人工智慧的最佳實踐和技術。該計劃的第三階段將是一個包含 15 個新聞業務的諮詢項目。

Event detection 事件偵測

We deploy a tool from SAM, a Canadian social media solutions company, to detect newsworthy events based on natural language processing (NLP) of text-based chatter on Twitter and other social media venues. SAM alerts expose more breaking news events sooner than human journalists could track on their own through manual monitoring of social media.
我們部署了加拿大社群媒體解決方案公司 SAM 的工具,根據 Twitter 和其他社群媒體場所上基於文字的聊天內容的自然語言處理 (NLP) 來偵測有新聞價值的事件。 SAM 警報比人類記者透過手動監控社群媒體自行追蹤的時間更快揭露更多突發新聞事件。

Image recognition 影像辨識

Image recognition software can improve the keywords on AP photos, including the millions of photos in our archive, and improve our system for finding and recommending images to editors. We have tested whether these tools can help keep graphic content out of our image feeds or help identify athletes by jersey numbers. This will create the first editorially-defined taxonomy for the news industry.

Automated stories 自動故事

Since 2014, we have automated text stories from structured sets of data using natural language generation (NLG). We began with corporate earnings stories for all publicly traded companies in the United States, increasing our output by a factor of 10 and increasing the liquidity of the companies we covered. We have since applied similar technology to over a dozen sports previews and game recaps globally.
自 2014 年以來,我們使用自然語言生成 (NLG) 從結構化資料集中自動生成文字故事。我們從美國所有上市公司的企業獲利故事開始,將我們的產出增加了 10 倍,並增加了我們所覆蓋公司的流動性。此後,我們已將類似技術應用於全球十多項體育賽事預覽和比賽回顧。

Automated shot lists 自動拍攝清單

We’re applying computer vision technology from Vidrovr to videos to identify major political and celebrity figures and to accurately timestamp sound bites. This is helping us streamline the previous process of manually examining our video news feeds to create text “shot lists” for our customers to use as a guide to the content of our news video.
我們正在將 Vidrovr 的計算機視覺技術應用於視頻,以識別主要政治人物和名人,並準確地為原聲摘要添加時間戳。這有助於我們簡化先前手動檢查視訊動態消息的流程,以建立文字“鏡頭清單”,供客戶用作新聞視訊內容的指南。

Real-time transcriptions

Software developed by Trint and employing machine learning is enabling us to transcribe videos in real time, slashing the time previously spent creating transcripts for broadcast video. We are now working to marry this technology with live video streams and also integrate automatic translation to multiple languages.


Watch the webinars below to learn more about artificial intelligence in the news industry.

ChatGPT & DALL-E: What Generative AI means for journalism

AI’s effect on search and your website visibility

AP Solutions: Five free AI projects for your newsroom

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